Tech Lead Manager, Machine Learning Frameworks

### **Minimum qualifications:**

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.

### **Preferred qualifications:**

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Expertise in ML compilers and runtimes.
• Experience with low-level programming.
• Experience with TPUs, TPU system design, GPUs.

**About the job**

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Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

Our team's vision is to help Cloud developers innovate Machine Learning (ML) supported products with effortless and transparent use of performant, efficient, effective, high-functioning ML infrastructure, focusing all their time and energy on forward-reaching achievements for products and the advancement of the field.

In this role, you will help build the ML infrastructure between frameworks and hardware to serve as a platform and operating system for ML programs.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

**Responsibilities**

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• Lead a team of engineers to develop end-to-end serving and training solutions for Google ML.
• Drive technical strategy and roadmaps for infrastructure development.
• Migrate existing frameworks (TensorFlow, JAX, PyTorch) runtimes (TFExecutor, TFRT, PJRT) and Product Areas (PA’s) custom workflows (AdBrain) onto ML Runtime, minimizing any user disruption.
• Identify and build stable, standardized APIs for internal products.
• Drive technical strategy and roadmaps for infrastructure development.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.